Genomic Characterization of Community-Associated Staphylococcus aureus Clinical Isolates to Inform Therapeutic Development
Poster #: 195
Session/Time: B
Author:
Amanda Lynn Yermal, MS, BS
Mentor:
Julia Sharp, PhD, MS
Research Type: Basic Science
Abstract
INTRODUCTION:
Staphylococcus aureus is a significant human pathogen capable of causing infections that range from mild to life-threatening. Pathogenesis is driven by S. aureus' adaptability, including the acquisition of antibiotic resistance genes and expression of virulence factors that facilitate immune evasion and host cell adhesion. Given this adaptability and increasing limitations of current treatments, ongoing surveillance and detailed characterization of circulating isolates are essential for identifying targets for novel anti-staphylococcal therapeutic development. Our lab maintains a library of over 200 community-associated S. aureus clinical isolates with associated metadata, 122 of which have previously undergone whole-genome sequencing. The present study aimed to further analyze these genomes and compare isolates across key group discriminators to better define the current S. aureus population and highlight potential therapeutic targets.
METHODS:
Whole-genome sequencing (WGS) datasets from S. aureus clinical isolates previously generated by the lab were used for genome assembly and analysis. Low-quality sequences were filtered and trimmed with Trim-Galore! (v0.6.10); contigs were assembled using SPAdes (v4.0.0). Contigs pre-generated with the Assembly module of the Local Run Manager (Illumina, San Diego, CA, USA) were used as references for contig scaffolding. Contig length and N50 values were used to gauge assembly quality. Custom AI-generated code was used to analyze and extract genomic information from the final assemblies, including strain-relatedness, presence of single nucleotide polymorphisms (SNPs), and characterize targeted genomic differences across multiple group discriminators. Analyses were extended to available genome sequences of select S. aureus isolates from the PubMLST database.
RESULTS:
Genome-wide analysis revealed phylogenetic relationships among isolates, conserved and emerging virulence factors, and enabled geospatial visualization alongside comparisons of other metadata.
CONCLUSION:
WGS enables comprehensive analysis of S. aureus isolates, surpassing traditional typing methods that offer limited resolution and genomic coverage. Analyzing the genomes of S. aureus clinical isolates currently present in the community provides insight into the characteristics underlying virulence and adaptability and lays a foundation for the development of novel anti-staphylococcal therapies.
Staphylococcus aureus is a significant human pathogen capable of causing infections that range from mild to life-threatening. Pathogenesis is driven by S. aureus' adaptability, including the acquisition of antibiotic resistance genes and expression of virulence factors that facilitate immune evasion and host cell adhesion. Given this adaptability and increasing limitations of current treatments, ongoing surveillance and detailed characterization of circulating isolates are essential for identifying targets for novel anti-staphylococcal therapeutic development. Our lab maintains a library of over 200 community-associated S. aureus clinical isolates with associated metadata, 122 of which have previously undergone whole-genome sequencing. The present study aimed to further analyze these genomes and compare isolates across key group discriminators to better define the current S. aureus population and highlight potential therapeutic targets.
METHODS:
Whole-genome sequencing (WGS) datasets from S. aureus clinical isolates previously generated by the lab were used for genome assembly and analysis. Low-quality sequences were filtered and trimmed with Trim-Galore! (v0.6.10); contigs were assembled using SPAdes (v4.0.0). Contigs pre-generated with the Assembly module of the Local Run Manager (Illumina, San Diego, CA, USA) were used as references for contig scaffolding. Contig length and N50 values were used to gauge assembly quality. Custom AI-generated code was used to analyze and extract genomic information from the final assemblies, including strain-relatedness, presence of single nucleotide polymorphisms (SNPs), and characterize targeted genomic differences across multiple group discriminators. Analyses were extended to available genome sequences of select S. aureus isolates from the PubMLST database.
RESULTS:
Genome-wide analysis revealed phylogenetic relationships among isolates, conserved and emerging virulence factors, and enabled geospatial visualization alongside comparisons of other metadata.
CONCLUSION:
WGS enables comprehensive analysis of S. aureus isolates, surpassing traditional typing methods that offer limited resolution and genomic coverage. Analyzing the genomes of S. aureus clinical isolates currently present in the community provides insight into the characteristics underlying virulence and adaptability and lays a foundation for the development of novel anti-staphylococcal therapies.